San Francisco, CA
Joined July 2010
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Truly, she’s one of the vilest. Just astonishingly and unfailingly awful.
She admits she gets a torrent of racist abuse, but engages in it herself. Despicable piece of shit.
She and Indian_Bronson, both cut from the same cloth.
I don’t know if I’m the best person to answer this. Build new stuff. There’s still a world of software that’s yet to be built. Start with any tool you use, and see how you can make it better. Ideas are cheap to try out. The more you do, the better you get at picking better ideas.
lol, I refuse to pay for this app, so typos shall remain.
It’s also how you know I’m rawdogging every tweet myself, rather than get AI to write it (which I learnt is a thing, esp with ultra long tweets some influencers and execs post)
Unfinished coding side projects are now way easier to complete than unfinished blog posts.
I’m perfectly OK with AI writing my code, even the docs.
But I flinch at the idea of AI writing my blog posts, which feels like an egregious violation of a fundamental ethnical contract.
Ideally the folks building software factories or harnesses should be evaluating how best to get agents to debug, because using Claude code out of the box isn’t going to cut it.
All super valid criticisms. I’m not a researcher or on a team at work that’s tasked with building better debugging primitives using evals, testing different mechanisms etc.
I’m just an infrastructure engineer who has access to claude, and am chronicling how I use it to debug.
That should be covered by the data integrity axis.
How data integrity is handled for stateful services which rely on replicated, partitioned data under different scenarios should answer most questions.
There are probably more patterns, but I need to go read more papers lol. Doing it will take time, hence the early 2027 (more like Feb or March) goal.
Lot of it holds up pretty well, actually.
The main changes in the last ~7 years have been in:
- move towards more flexible consistency
- use of replicated logs for all manner of things
- move away from strict consensus and synchronous replication
- control plane design choices
I started this series on testing nearly a decade ago, but never published the final part copyconstruct.medium.com/tes…
There’ve been so many great advances in the storage space in the ~7y I feel this is worth completing.
Have a draft from years ago I hope I can wrap up in early 2027.
Ok, so now I guess I have to do this lol.
Will try to get this done on Sunday, but if not, will have to wait until next weekend.
Might even blog, explaining where some of these ideas came from (specific senior devs I worked with, conf talks of the past, oss projects, etc)
It has both open and closed source test suites. SQLite is a library with multiple layers; all but one of the layers has oss test suites, iirc.
There’s plenty of great ideas in the open source test suites, covering a host of domains.
If that was your takeaway from that article, there’s no point engaging with you in good faith anymore. 👋
I’m literally that weirdo who wrote (all by hand) a 15K word blog post on:
- why one cant treat models as oracles
- how models gaslight you all the time
- what it takes to build confidence in the model’s output
copyconstruct.medium.com/how…
So yeah sure, I believe in magical woo-woo
None of this is true IME.
People who expect models to automatically do the right thing are bound to be disappointed. Give it good instructions, constraints, context and multiply verification by tenfold, and you get way better results than any human can achieve on their own.
Yes, and that’s why I have pre-commit review agents.
A swarm of them runs prior to every commit to each verify a separate design principle or guidance.
The edge cases are all handled comprehensively, it always tries at least two prototypes if not more before settling on the best design, which I never did, it has very rigorous pre-commit reviews, it runs a ton of microbenchmarks & mutation testing.
It writes better code than me.
Many projects for different reasons. SQLite for testing, llvm for layering + modular software design, scylladb for performant data structures, go std lib for canonical ways to handle/test http and other protocols, mpatterns in libraries like rust’s tokio, swift’s task/actors etc.
Might need to scrub some work specific stuff, but about 95% of it is just good general software engineering principles I’ve collected from the best sources I know (if I do say so myself).
I’ll try to make it public over the weekend.
To create my claude.md, I had it read:
- my favorite programming books + blogs
- the best oss projects
- the code of the engineers I respect the most
Claude (when given proper instructions, constraints, and context) now writes better code than me, almost always.
the coding agent haters are getting dunning-kruger'd so hard right now
do you really think that your engineering ability is better than the models at this point?
it is very very likely that fable is better than you in every branch of software
it has been trained on all the code of the internet, it knows almost every trick in the book, all the design patterns of every domain, every single low-level detail, every bit-twiddling hack, it's read every single blog post from every cracked engineer that ever existed
do you really think you can beat it? do you really think you can be more creative than it?
unless you are 99th percentile expert in some niche domain of software, it simply is not possible. sorry.